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Biometrika 2001 88(3):703-711; doi:10.1093/biomet/88.3.703
© 2001 by Biometrika Trust
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Computationally simple accelerated failure time regression for interval censored data

Rebecca A.Betensky1, Daniel Rabinowitz2 and Anastasios A.Tsiatis3

1 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, U.S.Abetensky{at}hsph.harvard.edu 2 Department of Statistics, Columbia University, New York, New York 10027, U.S.A.dan{at}wald.stat.columbia.edu 3 Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, U.S.A. tsiatis{at}stat.ncsu.edu

An approach is presented for fitting the accelerated failure time model to interval censored data that does not involve computing the nonparametric maximum likelihood estimate of the distribution function at the residuals.The approach involves estimating equations computed with the examination times from the same individual treated as if they had actually been obtained from different individuals. The dependence between different measurements obtained from the same individual is then accounted for in the calculation of the standard error of the regression coefficients. The approach is applicable to interval censored data in settings in which examinations continue to occur regardless of whether the failure time has occurred. Simulations are presented to assess the behaviour of the approach, and the methodology is illustrated through an application to data from an clinical trial.

Key Words: AIDS; Current status data; Nonparametric maximum likelihood; Survival analysis

Received June 1999. Revised February 2001


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